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Looks like eve: exposing insider threats using eye movement biometrics

Abstract:

We introduce a novel biometric based on distinctive eye movement patterns. The biometric consists of 20 features that allow us to reliably distinguish users based on differences in these patterns. We leverage this distinguishing power along with the ability to gauge the users’ task familiarity, i.e., level of knowledge, to address insider threats. In a controlled experiment we test how both time and task familiarity influence eye movements and feature stability, and how different subsets of f...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1145/2904018

Authors


More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Role:
Author
Publisher:
Association for Computing Machinery Publisher's website
Journal:
ACM Transactions on Information and System Security Journal website
Volume:
19
Issue:
1
Pages:
Article: 1
Publication date:
2016-01-01
DOI:
EISSN:
1557-7406
ISSN:
1094-9224
URN:
uuid:2c754b4d-afe3-47bd-827f-b448ed553750
Source identifiers:
619998
Local pid:
pubs:619998
Paper number:
1

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